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This study aimed to bibliometrically and visually analyze and review hospitality and tourism marketing studies published from 2000–2020.

A total of 3,942 articles collected from the databases of Social Science Citation Index (SSCI) and Science Citation Index Expanded (SCI-E) in the Web of Science (WoS) along with their references were used for analyses. The bibliometric software HistCiteTM and literature measurement visualization tools, VOSviewer and CiteSpace, were employed to analyze the selected articles.

The results of the study demonstrated top influential scholars and institutions, intellectual structure and emerging trends of the study topics, and future research opportunities in the field of hospitality and tourism marketing.

First, academic influence of a scholar was evaluated by citations of his/her publications, which did not take the order of authorship into consideration. Second, this study was restricted to the English language journals. Third, other types of published documents related to the studied field such as review papers were not considered by this research.

In comparison to traditional qualitative analysis such as content analysis, bibliometric analysis is a more objective approach to vividly demonstrate trends and performance of a research field, offers unique insights for its advancement with wider inclusiveness of a larger amount of data.

The purpose of this paper is to explore the correction mechanism of resilient safety culture on new generation of construction workers (NGCWs)' unsafe behavior and test the multiple mediation effects of job crafting and perceived work meaningfulness based on the context of Chinese construction industry in order to find a new way to effectively correct the NGCWs' unsafe behavior.

A theoretical model of correction mechanism was established based on literature research and theoretical deduction. An empirical study was employed based on confirmatory factor analysis and regression analysis with a sample of 404 NGCWs in China.

The results indicated that resilient safety culture can effectively correct NGCWs' unsafe behavior through job crafting and perceived work meaningfulness. Job crafting and perceived work meaningfulness can play independent and serial mediating roles between resilient safety culture and unsafe behavior.

Research results only represent a short-term law about the correction mechanism of NGCWs' unsafe behavior based on a questionnaire study from China's construction industry. It is necessary to continue to implement a longitudinal study to test it in a relatively long period in future research. The findings also need to be verified based on the young construction workers in other countries.

This study provides a theoretical basis and feasible management reference for construction enterprises in China to correct NGCWs' unsafe behavior from the perspective of resilient safety culture. Furthermore, the construction of resilient safety culture in construction enterprises can help NGCWs better carry out job crafting and perceive the meaning of work.

This paper clarifies the correction mechanism of resilient safety culture on unsafe behavior of NGCWs, and further tests the independent mediating roles and a serial mediating role of job crafting and perceived work meaningfulness between resilient safety culture and unsafe behavior, which fills the research gap about the influence mechanism of resilient safety culture on young construction workers' unsafe behavior and enriches the theoretical system of unsafe behavior correction of construction workers.

In recent years, personalized recommendations have facilitated easy access to users' personal information and historical interactions, thereby improving recommendation effectiveness. However, due to privacy risk concerns, it is essential to balance the accuracy of personalized recommendations with privacy protection. Accordingly, this paper aims to propose a neural graph collaborative filtering personalized recommendation framework based on federated transfer learning (FTL-NGCF), which achieves high-quality personalized recommendations with privacy protection.

FTL-NGCF uses a third-party server to coordinate local users to train the graph neural networks (GNN) model. Each user client integrates user–item interactions into the embedding and uploads the model parameters to a server. To prevent attacks during communication and thus promote privacy preservation, the authors introduce homomorphic encryption to ensure secure model aggregation between clients and the server.

Experiments on three real data sets (Gowalla, Yelp2018, Amazon-Book) show that FTL-NGCF improves the recommendation performance in terms of recall and NDCG, based on the increased consideration of privacy protection relative to original federated learning methods.

To the best of the authors’ knowledge, no previous research has considered federated transfer learning framework for GNN-based recommendation. It can be extended to other recommended applications while maintaining privacy protection.

Digital healthcare manages to grab considerable attention from people and practitioners to avoid severity and provide quick access to healthcare. Entrepreneurs also adopt the digital healthcare segment as an opportunity; nevertheless, their intentions to participate and encourage innovation in this growing sector are unexplored. Drawing upon the social capital theory and health belief model, the study examines the factors that drive entrepreneurship. A novel model is proposed to comprehend entrepreneurial intentions and behavior entrenched in social capital and other encouraging and dissuading perceptive elements with the moderation of trust in digitalization and entrepreneurial efficacy.

The cross-sectional method is used to collect data through a questionnaire from experienced respondents in China. The valid data comprises 280 respondents, analyzed by partial least square structural equation modeling.

Social capital significantly influences monetary attitude, and perceived risk and holds an inconsequential association with perceived usefulness, whereas monetary attitude and perceived usefulness meaningfully explain entrepreneurial activities. Perceived risk has a trivial impact on entrepreneurial intention. Entrepreneurial efficacy and trust in digitalization significantly explain entrepreneurial behavior and moderate the positive relationship between intention and behavior.

The present research proposes a novel research model in the context of entrepreneurship rooted in a digitalized world and offering new correlates. It provides valuable insights by exploring entrepreneurial motivation and deterring factors to get involved in startup activities entrenched in social capital, providing guidelines for policymakers and practitioners to promote entrepreneurship.